Investigating Parietal and Premotor Influence on Motor Cortical Excitability Associated with Visuomotor Associative Plasticity
Bibliographic record
Abstract
The brain changes in response to sensory signals it is exposed to. It has been shown that long term potentiation-like neuroplasticity can be experimentally induced via visual paired-associative stimulation (V-PAS). V-PAS combines afferent visual stimuli with a transcranial magnetic stimulation pulse to induce plasticity. Preparation of a reaching movement to generate activity in superior parietal occipital cortex (SPOC) was used in this study as an additional afferent contributor to modulate the resultant plasticity. We hypothesized that V-PAS with a reaching movement would induce greater cortical excitability than V-PAS alone and would exhibit facilitated SPOC to M1 projections. All four experiments enrolled groups of 10 participants to complete variations of V-PAS in a repeated measures design. SPOC to M1 projections facilitated motor cortex excitability following V-PAS regardless of intervention received. We did not observe evidence indicating extra afferent information provided an additive effect to participants. Investigation of PMd to M1 projections confirmed disinhibition and suggested interneuronal populations within M1 may be mechanistically involved. Future research should look to rule out the existence of an upper limit for effective afference during V-PAS and investigate the average influence of V-PAS on cortical excitability in the larger population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".